Vehicles carrying multiple passengers reduce fuel consumption, pollution, and highway congestion, relative to single-occupancy vehicles. Highway authorities provide various incentives for high occupancy vehicles which include allowing such vehicles to travel in traffic lanes limited to high occupancy vehicles (HOV lanes) and traffic lanes where a toll charged is reduced or eliminated for high occupancy vehicles (HOT lanes). Penalties are imposed on drivers of vehicles travelling with less than a predefined number of occupants (e.g., less than 2). Recent efforts have been directed toward sensing and image capture systems and methods to effectuate HOV lane enforcement. Manual enforcement of HOV/HOT lanes by law enforcement can be difficult and potentially hazardous. Pulling violating motorists over to issue tickets tends to disrupt traffic and can become a safety hazard for both the officer and the vehicle's occupant. Consequently, automated occupancy detection (i.e., the ability to automatically detect human occupants of vehicles), preferably coupled with automated vehicle recognition and ticket mailing, is desirable. Further development in this art is needed for automated solutions for determining the number of human occupants in a motor vehicle. While ordinary visible light can be used for vehicle occupancy detection through the front windshield under ideal conditions, there are shortcomings. For example, cabin penetration with visible light can be easily compromised by factors such as tinted windshields as well as environmental conditions such as rain, snow, dirt, and the like. Moreover, visible illumination at night may be distracting to drivers. Near infrared illumination has advantages over visible light illumination including being unobservable by drivers. Development in this art is ongoing as methods are need to analyze IR images captured of a moving motor vehicle and processing that image to determine a total number of human occupants in that vehicle. Vehicle occupancy detection methods often rely on prior knowledge of the reflectance spectrum of skin to determine a human occupant in an IR image. While such occupancy detection methods using skin spectral information in a multi-band camera system can give accurate occupancy detection, such methods require re-setting a value for a comparison threshold when environment conditions change.
Accordingly, what is needed in this art are increasingly sophisticated systems and methods which is robust to changing conditions by utilizing the spectral information of pixels of the driver to determine a threshold value used for pixel classification. The teachings hereof compliment previously disclosed pixel classification methods by Wang et al.